The energy transition has reached a stage where the pace of building new power sources is no longer the sole measure of progress. The outcome is increasingly determined by the grid’s capacity to receive, transmit and balance energy. Without data showing its actual condition, even modern infrastructure operates below its potential, and investment decisions are based on oversimplifications.
The scale of the problem is growing in line with energy demand. The International Energy Agency forecasts that global demand for electricity will increase by an average of 3.6 per cent per year until 2030. This growth will be driven by the electrification of industry and transport, heat pumps, data centres and the development of artificial intelligence. At the same time, over 2,500 GW of generation, storage and consumption projects are awaiting connection to the grid.
This is not merely a problem of insufficient transmission lines. Equally significant is the limited knowledge of their actual capacity, load and technical condition. Operators often have to adopt conservative limits because they do not have a complete picture of the infrastructure’s operating conditions. As a result, some of the available capacity remains unused.
Data increases the capacity of existing assets
The clearest example is the dynamic determination of line capacity, known as Dynamic Line Rating. The traditional model determines the permissible load based on fixed and conservative assumptions. The dynamic system uses data on conductor temperature, wind speed, solar radiation and weather conditions. On this basis, it calculates the actual transmission capacity at any given moment.
According to the IEA, this technology can increase the capacity of relevant sections of the grid by 20–30 per cent without the need to build new lines. Implementation usually takes less time than a conventional infrastructure project and requires incomparably less capital.
The US operator PPL used dynamic grid management to avoid a $12 million cable replacement project. At the same time, it reduced congestion-related costs by over $64 million. Oncor’s network achieved a 6–14 per cent increase in transmission capacity, whilst the Duquesne Light pilot project saw a 25 per cent increase.
These figures highlight the difference between the theoretical and actual availability of infrastructure. A lack of data leads to systems being designed for the worst-case scenario. Data enables the system to be managed in line with actual conditions.
Energy consumption is becoming an operational resource
Digitalisation is also changing the role of the consumer. Industry, warehouses, commercial buildings, data centres and electric vehicle fleets can respond to the situation in the system by shifting part of their consumption to periods of lower demand. Such flexibility has financial value, but requires accurate measurement data, automation and systems capable of controlling equipment in near real time.
The UK’s Demand Flexibility Service covered over 2.6 million customers in its first two years. Participants shifted over 7,000 MWh of consumption away from peak load periods. The mechanism did not involve restricting business activity, but rather coordinating consumption over time.
Enel’s pilot scheme in Colombia involved 21 companies, including those from the food and ceramics sectors. The companies provided 9.2 MW of flexible consumption, with a total base load of 12.1 MW. An analysis of the project indicated that grid investments worth over 48 million euros could be avoided.
Metering data is therefore beginning to fulfil a function similar to that of information on stock levels, production and financial liquidity. Without it, a company knows the amount of its bill, but cannot see which processes are generating the cost, when the risk of overload arises, or where there is scope for optimisation.
Poland is streamlining the energy data market
In Poland, a key element of this change is the Central Energy Market Information System (CSIRE). CSIRE began operations on 1 July 2025. Its task is to standardise data exchange between operators, suppliers and consumers, and to establish a common standard for handling processes in the retail energy market.
In July 2026, a further 72 entities joined the system. The migration covered 36,500 metering points, 99.8 per cent of which passed validation. The rate of transmission of daily consumption profiles exceeded 92 per cent.
The significance of CSIRE extends beyond facilitating smoother supplier switching or standardising billing. The system provides a foundation for dynamic tariffs, flexibility services, more accurate demand forecasting and automated consumption management. It also opens up the market to technology firms capable of integrating energy data with production, building and financial systems.
Data infrastructure is becoming critical infrastructure
Digital energy requires more than just the installation of meters and the construction of data warehouses. Consistent identifiers, high-quality measurements, system interoperability, resilience to failures and precise access rules are essential. Every new connection between the grid, an industrial plant, an energy storage facility and an analytics platform increases both the value of the data and the potential attack surface.
Therefore, the energy data architecture must be designed in parallel with cybersecurity, rather than having security measures added as an afterthought following implementation. An error in the reporting system distorts the data. An error in the control system can halt production, disrupt the grid or trigger costly safety measures.
The energy transition is not being held back by a lack of generation technology. Increasingly, it is constrained by a lack of reliable, up-to-date and accessible information about the grid. Data is not merely a digital overlay on the energy sector. It has become an integral part of its operational capability.
